Image Classification
Transformers
Safetensors
nula
computer-vision
cnn
cifar10
adversarial-robustness
stress-test
downsampling
anti-aliasing
custom_code
Instructions to use MamaPearl/nula-cifar10-robust-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MamaPearl/nula-cifar10-robust-v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MamaPearl/nula-cifar10-robust-v0", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("MamaPearl/nula-cifar10-robust-v0", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from MamaPearl/nula-cifar10-robust-v0: direct link, hf CLI and curl.
- Browser
- Download file 793 Bytes
-
https://huggingface.co/MamaPearl/nula-cifar10-robust-v0/resolve/b58ec66d89f2b1fca16dbeb7f43dcc7f6e3c85a5/config.json
- Command line
-
hf download hf://MamaPearl/nula-cifar10-robust-v0@b58ec66d89f2b1fca16dbeb7f43dcc7f6e3c85a5/config.json
-
curl -L -o config.json https://huggingface.co/MamaPearl/nula-cifar10-robust-v0/resolve/b58ec66d89f2b1fca16dbeb7f43dcc7f6e3c85a5/config.json
793 Bytes
Invalid JSON:Expected ':' after property name in JSONat line 39, column 14
| { | |
| "model_type": "NULA", | |
| "num_classes": 10, | |
| "in_channels": 3, | |
| "input_size": [3, 32, 32], | |
| "block_channels": [64, 128, 256], | |
| "use_residual": true, | |
| "use_se": true, | |
| "use_spatial_attention": false, | |
| "norm_layer": "batchnorm", | |
| "activation": "relu", | |
| "classifier_hidden_dim": 256, | |
| "init_scheme": "kaiming_normal", | |
| "dataset": "uoft-cs/cifar10", | |
| "mean": [0.5, 0.5, 0.5], | |
| "std": [0.5, 0.5, 0.5], | |
| "id2label": { | |
| "0": "airplane", | |
| "1": "automobile", | |
| "2": "bird", | |
| "3": "cat", | |
| "4": "deer", | |
| "5": "dog", | |
| "6": "frog", | |
| "7": "horse", | |
| "8": "ship", | |
| "9": "truck" | |
| }, | |
| "label2id": { | |
| "airplane": 0, | |
| "automobile": 1, | |
| "bird": 2, | |
| "cat": 3, | |
| "deer": 4, | |
| "dog": 5, | |
| "frog": 6, | |
| "horse": 7, | |
| "ship": 8, | |
| "truck:" 9 | |
| } | |
| } |